Development of Remote Condition Monitoring Platform for Heavy-Duty Diesel Engine

Condition monitoring (CM) and predictive maintenance (PdM) are essential for heavy-duty diesel engines, especially in variable-load/speed applications like rail, to enhance availability, reliability, and cost savings. In locomotive operation, non-steady operating conditions, high spare part costs, and imperfect maintenance procedures necessitate a shift from traditional, reactive maintenance to proactive failure prediction. This paper details the development and implementation of a remote condition monitoring platform specifically designed for the MAPNA-manufactured MDE-۱۶V۱۷R heavy-duty diesel engine used in the Iran-Safir locomotive. The system utilizes a hardware module to acquire operational data and transmit continues data packages to a central server via internet. The underlying principles of an algorithm employs Hybrid Methods, integrating engineering knowledge (Physics, Knowledge, and Experience-Based Models) and variable trend analysis to accurately diagnose deviations, and issue timely alerts. Examples include optimizing ECU protection thresholds, detecting fuel filter and oil-cooler clogging and diagnosing control valve operation. Total number of failures for the first three engines with the implementation of the pilot CM platform demonstrating the system's success in reducing unscheduled downtime, repair duration, and maintenance costs.

کلیدواژه ها:

remote condition monitoring ، heavy-duty diesel engine ، preventive maintenance